university-industry collaboration in computer science education and research eugene fiume university...

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University-Industry University-Industry Collaboration in Computer Collaboration in Computer Science Education and Science Education and Research Research Eugene Fiume Eugene Fiume University of Toronto University of Toronto [email protected] www.dgp.toronto.edu/ www.dgp.toronto.edu/ ~elf/.misc/tech.ppt ~elf/.misc/tech.ppt

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Page 1: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

University-Industry Collaboration University-Industry Collaboration in Computer Science Education in Computer Science Education

and Researchand Research

Eugene FiumeEugene FiumeUniversity of TorontoUniversity of Toronto

[email protected]/~elf/.misc/tech.pptwww.dgp.toronto.edu/~elf/.misc/tech.ppt

Page 2: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

There is a gulf between biggest questions in “practical” CS and those in “academic” CS. The primary aim of practical CS is the systematic development of reliable, economical, efficient, scalable, and usable software. The primary aim of academic CS lies in the creation of fundamental algorithms to settle scientific questions and for possible future application. I fear that despite considerable effort, the gulf between these two areas is widening, and our students, both undergraduate and graduate, are falling into it. The academic pressures of tenure and promotion also tend to reward research of more immediate scientific impact than the rigours of developing a long-term multi-disciplinary software research agenda that necessarily involves human dynamics and communications.

In this talk, we shall use this context as a point of departure to explore the broader issue of enhancing the collaboration between University and Industry. While I have no magic solutions to offer, but I will draw on my experiences in technology transfer, software development, and research management to illustrate that it may in fact be possible to bridge the gulf while respecting the separate agendas of university and industry.

AbstractAbstract

Page 3: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Relevant BiographyRelevant Biography• Professor & Past Chair of Dept of CS at U of Toronto.Professor & Past Chair of Dept of CS at U of Toronto.

• Personal involvement in technology transfer projects.Personal involvement in technology transfer projects.

• Directed Research and Usability Engineering at Alias|Directed Research and Usability Engineering at Alias|Wavefront, and directed University Relationships.Wavefront, and directed University Relationships.

• Advisor to companies and VCs in digital media, internet Advisor to companies and VCs in digital media, internet services, software strategy, corporate organisation.services, software strategy, corporate organisation.

• Heavily involved in intellectual property issues.Heavily involved in intellectual property issues.

• Member of many Scientific and Corporate Boards.Member of many Scientific and Corporate Boards.– Policy issues on IP repositories.Policy issues on IP repositories.

– ““Success” measures for research.Success” measures for research.

– Matching innovation (research outcomes) to business/societal Matching innovation (research outcomes) to business/societal impact.impact.

Page 4: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

OverviewOverview

• The two sides: IT in University and Industry.The two sides: IT in University and Industry.

• The gulf between them.The gulf between them.

• Bridging the gulf.Bridging the gulf.

Page 5: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Warning!Warning!

DeliberateDeliberate

oversimplificationsoversimplifications

toto

follow.follow.

Page 6: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Simply PutSimply Put

A university’s obligation is to the betterment A university’s obligation is to the betterment of society through discovering, preserving, of society through discovering, preserving, and disseminating knowledge.and disseminating knowledge.

A corporation is responsible for maximising shareholder value and increasing the material prosperity of its employees and of society.

From the beginning, there is a gulf to bridge.

Page 7: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

ImplicationsImplications

University education and technology University education and technology transfer both tend to be far more finely transfer both tend to be far more finely focused than the available diversity.focused than the available diversity.

Industry needs broader skills from its Industry needs broader skills from its employees and partners to build products employees and partners to build products and solutions, not technology.and solutions, not technology.

We have a gulf in practice as well.We have a gulf in practice as well.

Page 8: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

University CS (and CE)University CS (and CE)

Difficult to generalise, but University research:Difficult to generalise, but University research:

• is about fundamental algorithms and results.is about fundamental algorithms and results.• has multiple year horizon.has multiple year horizon.• aims to affect the future through disruption.aims to affect the future through disruption.• is risk tolerant (but what about tenure?).is risk tolerant (but what about tenure?).• has highly orthodox structures.has highly orthodox structures.• is peer reviewed.is peer reviewed.• is not usually “integrative” in the short term.is not usually “integrative” in the short term.

Page 9: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Industrial CS (and CE)Industrial CS (and CE)

Difficult to generalise, but Industrial R&D:Difficult to generalise, but Industrial R&D:

• focuses on feasible realisations.focuses on feasible realisations.• has 1-2 year horizon.has 1-2 year horizon.• aims to affect the future through evolution.aims to affect the future through evolution.• is risk prudent.is risk prudent.• has evolving structures.has evolving structures.• hierarchical and peer-based validation.hierarchical and peer-based validation.• is “integrative”.is “integrative”.

Page 10: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

““Integrative?”Integrative?”

• That innovation is mapped out in advance to That innovation is mapped out in advance to accumulate and support a specific objective.accumulate and support a specific objective.

• Ongoing basic research is not in principle Ongoing basic research is not in principle integrative in that new, serendipitous results integrative in that new, serendipitous results can completely change research focus.can completely change research focus.

• However it However it is is integrative in the long term.integrative in the long term.

• ““Applied” research and development is Applied” research and development is integrative as smaller results should integrative as smaller results should aggregate into a unified, cohesive outcome.aggregate into a unified, cohesive outcome.

Page 11: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

University CS (and CE)University CS (and CE)

Difficult to generalise, but CS education:Difficult to generalise, but CS education:

• is about implementing fundamental algorithms.is about implementing fundamental algorithms.• focuses on “inside-out” software development.focuses on “inside-out” software development.• deals with computers as abstractions.deals with computers as abstractions.• promotes abstract complexity measures over promotes abstract complexity measures over

practical performance and usability.practical performance and usability.• emphasises individual performance.emphasises individual performance.• produces outstanding, focused technical grads.produces outstanding, focused technical grads.• whither communication, business, culture?whither communication, business, culture?

Page 12: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Industrial CS (and CE)Industrial CS (and CE)

Difficult to generalise, but needs:Difficult to generalise, but needs:

• to develop reliable, robust, usable products.to develop reliable, robust, usable products.• to focus on outside-in product development.to focus on outside-in product development.• to see computers as concrete things.to see computers as concrete things.• to promote practical performance. to promote practical performance. • to emphasise team performance.to emphasise team performance.• a combination of technical, business, cultural.a combination of technical, business, cultural.

Page 13: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Implications: Technology TransferImplications: Technology Transfer

University-based researchers:University-based researchers:

• tend to over-value individual focused results.tend to over-value individual focused results.• do not see intellectual property as accretive.do not see intellectual property as accretive.• have an incomplete understanding of market have an incomplete understanding of market

and industry.and industry.• underestimate cost of integration/deployment.underestimate cost of integration/deployment.• are better scientists than entrepreneurs.are better scientists than entrepreneurs.• do not see their universities as helpful in TT.do not see their universities as helpful in TT.

Page 14: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Implications: Technology TransferImplications: Technology Transfer

Industrial R&D:Industrial R&D:

• even internal TT is difficult!even internal TT is difficult!• underestimates importance of grad students. underestimates importance of grad students. • underestimates the analytic skills of academics:underestimates the analytic skills of academics:

– Academics are paid to think and they do it well!Academics are paid to think and they do it well!– Excellent advisors and reviewers.Excellent advisors and reviewers.– Views academics as too “ivory tower”.Views academics as too “ivory tower”.

• does not appreciate societal role of university.does not appreciate societal role of university.• does not appreciate the potential of interaction:does not appreciate the potential of interaction:

– Celebrate the differences!Celebrate the differences!

Page 15: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

The Innovation “Pipeline”The Innovation “Pipeline”

Basic Basic ResearchResearch

Applied Applied ResearchResearch

IndustrialIndustrialR&DR&D

Product Product IntegrationIntegration

Outcomes:Outcomes:• gradsgrads• demodemo• paperspapers• grantsgrants• awardsawards• presspress

Outcomes:Outcomes:• prototypeprototype• patentspatents• licenceslicences• TTTT• matchingmatching fundsfunds

Outcomes:Outcomes:• prod designprod design• consultconsult• financingfinancing• biz planbiz plan

Impacts:Impacts:• to societyto society• revenuerevenue• wealthwealth• well-beingwell-being

Increasing resources spent (but must reduce cost)Increasing resources spent (but must reduce cost)

UniversityUniversity

IndustryIndustry

TT happens only when cost, people, timing are right.TT happens only when cost, people, timing are right.

Page 16: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Suggestions: Technology TransferSuggestions: Technology Transfer

• Don’tDon’t force research to be commercialisable! Disaster! force research to be commercialisable! Disaster!• BelieveBelieve in the scientific method: it is robust and redundant. in the scientific method: it is robust and redundant.• Provide greater opportunity for serendipitous TT.Provide greater opportunity for serendipitous TT.• Research-industry discussion forums without IP preconditions.Research-industry discussion forums without IP preconditions.• New funds for TT separate from basic research funding.New funds for TT separate from basic research funding.• Reward university-industry interaction, especially through Reward university-industry interaction, especially through

programmes involving people transfer in performance reviews.programmes involving people transfer in performance reviews.• Provide more business mentoring to researchers.Provide more business mentoring to researchers.• Reduce barriers to TT through better IP ownership policies.Reduce barriers to TT through better IP ownership policies.

– Make more money on philanthropy over research royalties!Make more money on philanthropy over research royalties!

• Put deployment cost models into seed-funding VC structure:Put deployment cost models into seed-funding VC structure:– Industrial tech transfer is never in VC funding plan. Why not?Industrial tech transfer is never in VC funding plan. Why not?

Page 17: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Evolution of Industrial Software ProductsEvolution of Industrial Software Products

Large,Large,monolithicmonolithicback officeback officeapplicationsapplications

Browser-based toolsBrowser-based tools

Web services, SOAWeb services, SOA

Interactive analysis Interactive analysis (Business Intelligence)(Business Intelligence)

Data Analysis, Data Analysis, Data MiningData Mining

Greater exposure to software and data components.Greater exposure to software and data components.

Increasingly collaborative, interactive.Increasingly collaborative, interactive.

Page 18: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

““Software Engineering”Software Engineering”

We have been speaking here ofWe have been speaking here of

Product Development.Product Development.

However one defines “software engineering” :However one defines “software engineering” :

SE is a subset of PD!SE is a subset of PD!

AndAnd

PD is a subset of “Business Models and Processes”.PD is a subset of “Business Models and Processes”.

Page 19: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

The Changing Product LandscapeThe Changing Product Landscape

TechTechR&DR&D Feasibility Feasibility and devand dev

UserUserSupportSupport QAQA

OpsOpsProcsProcs Capacity Capacity PlanningPlanning

UIUIworkflowworkflow UI DesignUI Design MktgMktgCollateralCollateral Brand, Brand, positionposition

CIOCIODBDB AssetsAssets

SalesSalesShowsShows DealsDeals

CFOCFOFundsFunds GovernanceGovernance

CTO, CTO, legallegal

M&AM&A DDDD IP & TTIP & TT

Only a tiny Only a tiny subset of subset of the the linkages linkages are are indicated.indicated.

Page 20: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Departmental LinkagesDepartmental Linkages

• They have always existed.They have always existed.• But they’re tighter now.But they’re tighter now.• Many stakeholders, including customers.Many stakeholders, including customers.• More third party arrangements (e.g., TT).More third party arrangements (e.g., TT).• More multi-site engagements (e.g., M&A).More multi-site engagements (e.g., M&A).• Communication becomes a crucial problem.Communication becomes a crucial problem.• Need to share diverse knowledge.Need to share diverse knowledge.

““Agile” management techniques?Agile” management techniques?

Page 21: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Business Implications?Business Implications?

• Different expertise needed.Different expertise needed.• Far more early communication and discussion.Far more early communication and discussion.• Fast due diligence and technology transfer.Fast due diligence and technology transfer.• More “strategic” partnerships.More “strategic” partnerships.• Less direct development (e.g., outsourcing).Less direct development (e.g., outsourcing).• More integration, component based design.More integration, component based design.• Different management styles, incentives.Different management styles, incentives.• Stronger business and customer focus.Stronger business and customer focus.• Cleaner business and development processes.Cleaner business and development processes.

Page 22: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Business Expectations of StudentsBusiness Expectations of Students

• Cannot assume “out of box” performance.Cannot assume “out of box” performance.

• More mentorship and apprenticeship (trades).More mentorship and apprenticeship (trades).

• More ongoing professional development.More ongoing professional development.

• University training is a beginning, not an end.University training is a beginning, not an end.

• Need broader array of University/Industry Need broader array of University/Industry engagements (co-ops, internships, exchanges, engagements (co-ops, internships, exchanges, joint research, joint development, joint research, joint development, consultancies, contracts).consultancies, contracts).

Page 23: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

University Implications?University Implications?• There is too much to teach, too little time – continuing educ.There is too much to teach, too little time – continuing educ.• Students still need strong science/tech core.Students still need strong science/tech core.• But undergraduates need more communications, business, But undergraduates need more communications, business,

project mgmt, design, usability, humanities.project mgmt, design, usability, humanities.• Separate technical features from real business need.Separate technical features from real business need.• Graduate students could use a unit of business school.Graduate students could use a unit of business school.• Increased exposure to users, customers, systems integration, Increased exposure to users, customers, systems integration,

capacity planning, performance, bandwidth, latency, usability.capacity planning, performance, bandwidth, latency, usability.• Must learn more about corporate structures (SOX).Must learn more about corporate structures (SOX).• More team-based project work.More team-based project work.• More professional UGrad/Grad programmes?More professional UGrad/Grad programmes?

Page 24: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

Curriculum ImplicationsCurriculum Implications

• So many masters, so much diversity!So many masters, so much diversity!

• More streams to address diversity.More streams to address diversity.

• Need more people in the field (especially women).Need more people in the field (especially women).

• Case-based, “capstone” programmes?Case-based, “capstone” programmes?• Differentiated professional programmes.Differentiated professional programmes.• Senior management programmes (like EMBA):Senior management programmes (like EMBA):

– Career path limitations for 2Career path limitations for 2ndnd/3/3rdrd line tech managers. line tech managers.

• Multiple academic unit combined programmes.Multiple academic unit combined programmes.

Page 25: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

““Capstone?”Capstone?”

Definition:Definition:

• The top stone of a structure or wall.The top stone of a structure or wall.

• The crowning achievement or final stroke; The crowning achievement or final stroke; the culmination or acme.the culmination or acme.

Provide design based, team-work oriented Provide design based, team-work oriented final courses that facilitate transition to final courses that facilitate transition to industrial careers. Focus on users, products, industrial careers. Focus on users, products, negotiation, “outside-in” development.negotiation, “outside-in” development.

Page 26: University-Industry Collaboration in Computer Science Education and Research Eugene Fiume University of Toronto elf@dgp.toronto.edu elf/.misc/tech.ppt

ConclusionsConclusions

• The gulf is wide but can be bridged.The gulf is wide but can be bridged.• Need a clearer understanding of each side.Need a clearer understanding of each side.• Need to look at the obstacles and react to them.Need to look at the obstacles and react to them.• Respect for their traditional roles.Respect for their traditional roles.• Focus on building grass-roots relationships:Focus on building grass-roots relationships:

– formal agreements come later.formal agreements come later.– discussion is at least as valuable as the technology.discussion is at least as valuable as the technology.– graduate students are key.graduate students are key.